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Shaw Wu of American Technology Research has chimed in with his predictions for next week’s special Apple event on September 9 – warning it could be “underwhelming”.
“We continue to believe that MacBook Pro and MacBook are due for refreshes with more radical redesigns, but won’t likely be unveiled at this event as the focus appears to be on its non-Mac businesses,” he also observed.
Not so underwhelming to matter a great deal – at least, not to Wu, who chose to maintain his Buy rating and 6-12 month price target of $220. We considered rewriting this release with our own special slant, but figured you may want it straight – here’s what Wu writes…
Low Expectations for a Break-Through Announcement:
While there is always room for surprise, it seems this event may be somewhat underwhelming vs. previous expectations and events. Over the past several days, AAPL shares have pulled back as expectations have likely come down.
Likely iPod Centric:
The “Let’s Rock” invitation and our recent supply chain checks suggest this will likely be an iPod-centric event. This may be viewed as disappointing as some were hoping to see new Macs. We think radical changes in the iPod portfolio are less likely given the great success and extensive refinement iPod has already undergone. We anticipate a modestly redesigned 4th generation iPod nano and slimmer 2nd generation iPod touch with lower price points and higher storage capacities. The future of the 6th generation iPod classic is unclear as our checks indicate build plans have been more modest as it has become more a niche product.
New Macs Not Likely At This Event:
We continue to believe that MacBook Pro and MacBook are due for refreshes with more radical redesigns, but won’t likely be unveiled at this event. We are picking up that MacBook Air could see a minor refresh and potential price cut to increase its value proposition. Checks indicate that build plans have slowed somewhat from earlier robust levels with customers opting for MacBook or MacBook Pro.
We believe wildcards on new products are:
2) new touch form factors (iPod-Mac hybrid) with larger screens.
While AAPL shares will likely remain volatile given market sentiment, we view current levels as a buying opportunity for longer-term investors. AAPL remains one of the best positioned large-cap technology companies. We see upside to $220 based on 32.5x our CY09 EPS of $6.73.
Event Likely Less Surprising But There Is Always Room for the Unexpected:
New iPods Most Likely:
Our recent supply chain checks indicate that this event will most likely usher in new iPods, including a modestly redesigned 4th generation iPod nano and slimmer 2nd generation iPod touch with lower price points and higher storage capacities. The fate of its 6th generation iPod Classic is unclear as build plans have been more modest. We think this product remains attractive to those users who value high-capacity storage (80 and 160 GB), but the “old” design and cannibalization by iPod touch limit its appeal.
New Macs Not Likely At This Event:
We continue to believe that MacBook Pro and MacBook are due for refreshes with more radical redesigns, but won’t likely be unveiled at this event as the focus appears to be on its non-Mac businesses. In addition, we are picking up that MacBook Air could see a minor refresh and potential price cut to increase its value proposition as build plans have slowed from earlier robust levels as customers have opted for MacBook or MacBook Pro instead.
Lower iPod Price Points Make A Lot of Sense.
In this tough macroeconomic environment, we believe price cuts make a lot of sense to re-accelerate iPod sales, particularly iPod touch, which is somewhat mispriced (outside of its recent back-to-school promotion) at $299 (8 GB), $399 (16 GB), and $499 (32 GB) price points given the lower $199 (8 GB) and $299 (16 GB) price points of the 3G iPhone with 2-year service plans. We believe AAPL should be able to absorb lower price points without impacting its margins materially given very favorable component pricing trends.
Competitive Advantages Intact:
Macro headwinds are becoming more apparent:
We continue to see AAPL as the best play on digital media in the home and a large beneficiary of the shift to mobile computing. In two of its three big franchises, Mac and iPhone, penetration is very low and starting in the higher-income demographics. The disturbance in the macroeconomic environment is within lower-income demographics and financial institutions with exposure and impact to overall liquidity. This could certainly spread, but we believe AAPL’s business will remain strong in the near- to medium-term. Enough high-end consumers are still buying tech, though commodities inflation could pressure future margins.
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According to the Bureau of Labor Statistics (BLS), the employment of research analysts, including data analysts, is projected to increase by 23% from 2023 to 2031. This significant growth in data analysis careers presents promising prospects for aspiring candidates. It profoundly impacts the services and products provided to the public. As a data analyst, you must possess problem-solving and analytical skills and technical knowledge of computer science, statistics, and mathematics. This field offers ample opportunities for personal and professional growth, allowing you to work with cutting-edge technologies. But what exactly does this exciting career path entail? Let’s explore the expectations placed upon an ideal candidate providing data analysis services to a company.What Does a Data Analyst Do?
Data analysis refers to gaining information from data or analyzing it to use it for business benefit. It provides quality insights with crucial points that direct the company’s decision-making process. The job’s roles and responsibilities include:
Gathering data for analysis. It will involve discovering or collecting different types of data through various modes. Examples include surveys, polls, questionnaires, and tracking the visitor characteristics on the website. Alternatively, the datasets can be purchased depending on the requirement and availability.
Programming languages perform the cleaning process on the data generated after the previous step, called raw data. The name implies the presence of unwanted information, including outliers, errors, and duplicates, that require processing. The cleaning process aims to enhance the quality of the data and make it usable.
The data needs to be modeled now by providing it with a structure and representation in an organized manner. It will also involve categorizing data and other relevant processes to make it presentable.
The data thus formed will serve multiple purposes. The usage will depend on the problem statement, which will also determine the method of interpretation. Data interpretation mainly involves finding trends or patterns in data.
Presentation of data is an equally important task where the prime requirement is to let the information reach the viewers and involved parties in the same way as intended. It requires presentation and communication skills. Often data analysts take the aid of charts and graphs, followed by report writing and information presentation.
Source: ForageReasons to Become a Data Analyst
Multiple reasons can encourage one to become a data analyst. The five most important ones are:
High demand: The rise in data generation has led to tons of unprocessed data. It holds numerous secrets that the companies can use. The requirement for individuals who can carry out the task is growing exponentially, with the standard requirement of 3000 positions annually.
High pay: The pay scale for a data analyst position is high and worth pursuing the career. The pay rise varies according to the industry and promises higher incomes with bonuses in some fields.
Lead the career choice: The skillful data analyst is set to bring value to the position and company. The possibility of growth, promotions, and additional benefits remains open everywhere. It positions you to get a change, lead the groups, teach them, become competitive, or shape the workforce culture.Demand and Future Job Trends
The current demand for data analysts is high at a good pay scale. The requirement in the future is also expected to grow based on the current speed of data generation. With the generation of new technologies and ease of data collection, the future will surely provide new opportunities to the talents. Some of the expected new job roles for data analysts in the future include:
Explain the functionality and suitability of AI. Quality analysis of the newly developed functions.
Working on a combination of real-time analytics in business operations and data processing. It will guide toward planning based on logic and strategy.
Generated data interpretation reports need to be self-explainable and easy to interpret. Data visualization is crucial, and the field holds good career scope.
Expect the introduction of augmented analytics, where complex datasets can be handled via ML algorithms and NLP algorithms. It will be engaging and universally accessible.
Development of Machine Learning and the Internet of Things to ensure the possibility of currently impossible things is also expected to occur.
Source: College VidyaSpecializations in Data Analyst Field
The data analyst position offers specific fields to work in. The different specializations to look forward to include:
Source: Online ManipalRisk Analyst
It includes working for money-based companies such as financial institutions and insurance companies. Their work is mainly focused on predictions based on the data. The risk analyst must go through economic conditions, financial documents, and other things as per the requirement.Budget Analyst
They are generally found to work in businesses or industries to assist in analyzing downward and upward trends. Typical examples of this sector include private businesses, educational institutions, and government-based institutions. The work here also is dependent on financial situations and documents.Operation Analyst
These job profiles are concerned with finding solutions to the problems in business. The specific focus here is on operations which can include different projects, manufacturing, or any other operation problem in the company.Research Analyst
They are concerned with research and deep insight into the available data. The research analyst has to deal with market information and extract information for investment, selling, and designing future strategies. The financial, investment, and equity expertise are of focus here.Marketing Analyst
It involves a sole focus on market conditions with an emphasis on trends, requirements, and needs of customers. It includes products and services, the target audience, and the ideal price for the company’s offerings.Business Intelligence Analyst
Business Intelligence Analyst analyzes complex data sets to provide insights and make data-driven recommendations for business improvement. They develop and maintain dashboards, reports, and data models, ensuring accurate and timely information. Their role involves translating data into actionable insights to support strategic decision-making and drive business success.Healthcare Analyst
The field is basically for a healthcare system that includes hospitals and pharmaceutical companies. The work here broadly focuses on public health, clinical information, pharmaceuticals, claims, costs, patient behavior, and satisfaction. The ultimate aim is to improve the process.8 Must Have Skills to Become a Data Analyst
The candidates looking for data analyst roles must have technical and professional skills.
Source: Rocket RecruitingTechnical Skills 1. Knowledge of Database Tools Such as Microsoft
Microsoft Excel helps summarize and simplify the data through pivot tables and provides fascinating representation methods, commands, and add-ins or additional features to handle the data. SQL helps manage data in relational databases, interpretation, reading, and manipulation.2. Ability to Work with Programming Languages Such as R or Python
Knowledge of programming languages is required for statistical analysis, machine learning, web development, data manipulation, and integration with web applications to simplify complex mathematical problems and data processing.3. Good Presentation Skills to Present the Interpreted Data
It involves using software like Jupyter Notebook and Tableau. They aid by providing interactive and dynamic visualization and helping curate dashboards and reports. Helping with data exploration, analysis, and iterative development allows independent running of code cells and debugging.4. Information and Application Ability of Statistics and Mathematics
Statistics serve to summarize and describe the data through variability, correlation, central tendency, and identification of patterns. Mathematics contributes to algorithm development and data modeling, providing concepts of linear regression, probability, and multiple significant theories.Professional Skills 6. Ability to Have a Passion for Solving the Problem and Overcoming Challenges
Dealing with a wide variety and high amount of data will pose a challenge. The demands and problems will vary with no solution. The analytical and problem-solving mindset will help you overcome them without looking for existing answers. It will help you create the solution.7. Communicate Clearly and Precisely
Data visualization is crucial in data analysis. However, it must be communicated effectively to the team members, seniors, management, and other involved authorities for easier and clearer interpretation. The inability to clarify them will decrease the value of your work leading to your efforts in vain.8. Core Knowledge of the Industry
Data analysis is applicable in a wide array of industries. Working in a specific industry, for instance, healthcare will make you come across medical terms. Familiarity with them will ease the workflow and increase the efficiency of results and work.
Data analysts have to work online. The different involved responsibilities require a variety of tools and proficiency in them. The important ones are:SAS
SAS or Statistical Analysis Software is used for statistical modeling. It allows data processing and manipulation by providing comprehensive procedures, functions, and data programming technology. SAS allows description, inferential statistics and regression, time series, and survival analysis which serves in the analysis procedure. It also contributes to visualization and data mining through information charts, plots, and graphs with customization options. Data analysts also use SAS to handle large-scale datasheets by efficiently subsetting, sorting, and merging the data.
Source: SAS InstituteMicrosoft Excel
Source: Learning computerSQL
The software is primarily used by Data Analysts while dealing with relational databases. They need it to retrieve, manipulate and filter the data for aggregations, joining multiple tables and calculations. The SQL allows data transformation into different data types and the creation of new derived columns. It also provides basic functions similar to Excel. One of the characteristic features here is the WHAT clause to find the data based on search criteria like inclusion or exclusion of specific ranges or values and logical conditions. Besides, data analysts use SQL for defining indexes, modification of database structures, security and permission management, and optimizing query performance.
Source: Microsoft LearnJupyter Notebooks
It is a web-based application highly beneficial and efficient for data analysts in their tasks like creating and sharing documents comprising live code and narrative texts. Jupyter Notebook provides an interactive environment through the possibility of writing and executing code in different programming languages. It is integrated with significant analytical libraries, such as NumPy, pandas, and scikit-learn in Python useful for statistical and machine learning. Some visualization-based libraries include Seaborn, Matolotlib, and Plotly. It has the characteristic feature of reproducibility, a flexible learning environment, and integration services such as APIs and cloud platforms.
Source: JupyterGoogle Sheets
Source: GoogleR or Python
The programming languages R and Python serve different purposes: R aids in statistical computing and analysis, while Python is widely employed for general-purpose programming. Python is preferable for integrating external sources and its vast library, resources, and tools specifically designed for data analysis. Both machine learning and data analysts use R and Python through their packages like xgboost, caret, scikit-learn, and TensorFlow. Data analysts utilize them for data manipulation, visualization, analysis, and transformation.
Source: TableauMicrosoft Power BI
It is a business intelligence tool that helps in processing the raw data. Microsoft Power BI provides a wide variety of features. It allows data exploration and analysis. Advanced analytics options such as Azure Machine Learning and Cognitive Services help with data analysts in sentiment analysis and incorporation of machine learning models. It also aids natural language processing, interactive dashboards creation, and custom visuals. The tools come coupled with mobile-friendly access to the program. The responsive designs are flexible and adjustable according to different devices and screen sizes, allowing non-stop working on the go. It also supports row-level security and role-based access control.
No career is made in a day. It requires discipline and consistency to set your foot strong in any field. The driving factor or purpose of going into the career is the key to remain consistent and continue working hard. Be it any phase of life, gaining knowledge is easy now. Regardless of background, you can choose the right career path to reach the goal of becoming a data analyst. You might consider being a data analyst a good job. The answer to this lies in your passion and will to make a career out of it. If you love different aspects of this job, you will never have to ask yourself if being a data analyst is good. Head on to learn, through Certified AI and ML Blackbelt program offered by Analytics Vidhya to know if data analytics is a good career.Frequently Asked Questions
Q1. How can I become a data analyst?
Ans. If you are at the school level, select math and statistics subjects. Further, pursue a bachelor’s degree in statistics, computer science, math, or others. Gain experience through internships and polish your skills with professional certificates. People wishing to switch fields can also gain professional certifications and enter their careers.
Q2. What is the salary of a data analyst in India?
Ans. The average data analyst salary in India is around 6 lakhs per year. The additional average compensation is around INR 75,000.
Q3. Does a Data analyst come into an IT job?
Ans. Yes, data analysis is part of the IT job. It requires mathematical and computer science skills, which are technical.
Q4. Are data analysts and data scientists the same?
Ans. No, though the positions hold similarities, the job profiles and responsibilities for both are different. Data analysts interpret the data to derive meaningful information, but data scientists focus on complex statistical models and algorithms for pattern identification and predictions.
Q5. Is data analysis a good job?
Ans. Data analysis is a good job with numerous opportunities. It is a demanding career profile with a good pay scale.
Q6. What are the types of data analysis in business?
Ans. Four types of analysis are done on the data to serve the business. It includes descriptive, predictive, diagnostic, and prescriptive analysis.
Over last 6 years, I have come across more than hundreds of analysts and have conducted almost equal number of interviews. Over this time, I have developed a knack of differentiating best analysts from good and good analysts from bad. If you face this challenge regularly, this post might help you.
So how do you differentiate between good and bad analysts?
Thankfully, it’s not that difficult. I have put a framework around how to judge an analyst. You can use the same to make your life simpler. This framework has it’s genesis in hiring guidelines at Capital One. I have modified it to adopt it in Indian Analytics industry.
This is the most important attribute that distinguishes a good analyst from bad. This attribute is not only required to be a successful analyst, it becomes absolutely critical for a person managing Business Analysts.
So what is Structured thinking?
Structured thinking is a process of putting a framework to an unstructured problem. Having a structure not only helps an analyst understand the problem at a macro level, it also helps by identifying areas which require deeper understanding.
How do I test for structured thinking?
Typically I test this by throwing a open business problem at an analyst and then observing closely how he / she is solving it.
An example is asking a question like: “You have been appointed as CEO of a loss making restaurant at Delhi / London Airport and you are expected to join the company in a week. What would you want to do as a CEO of the company as soon as you join them?”
If the person lays out a nice structure about where the problems could be, he has already ticked one box. If he starts giving you answers out of his hat (e.g. I would be looking at what marketing are we doing?), you should consider it as a red flag. He will not be able to sail through the world of Analytics.
Business understanding and problem solving
There is a reason why Business Analysts are called so and not just Analysts. Until a person understands what he is trying to solve and the business owners are confident that he can solve problems in meaningful manner, he is a dead analyst.
So, how do you test for business understanding?
For an experienced analyst, I typically start judging this by asking about business context for the projects he might have worked on. If he can explain that clearly, it’s a good start. If he can’t, you can almost make your hiring decision here. Next, you can look at the answers a person gives in response to question asked for judging structured thinking. If he gives answers based on numbers only, you need to probe him further. He needs to put a business thinking hat and provide some out of box suggestions.
Attention to details
If a person is not detail oriented, he can never be a good analyst. Every analyst should have the ability to understand business at high level, but he should be able to get down to nuts and bolts of all the levers you might have.
So how do you judge for attention to details?
Start by looking at the CV of a person, has he spent time choosing words carefully? Has he mentioned impact of the projects he might have worked on?
For an experienced analyst, probe on the projects he might have worked on before. Did he consider all the aspects and possibilities? How much time does take to explain his previous projects?
Another way to judge it is by asking the candidate to a guess estimate, something like “Estimate the number of smartphones used in India” and looking at how the candidate answers them. How many factors does he consider to come up with answers? How many segments does he consider to arrive at sizing? These aspects should give you a good read on how detail oriented a person is.
Ability to triangulate numbers & do back of the envelope calculations
While the first three characteristics help you identify a better than average analyst, this characteristic and the next differentiates best of analysts from good analyst. This is an activity I love to do and something I know every good analyst loves. This is the ability to set up equations on page and then do back of the envelope calculations to answer 80% of questions without touching any excel / calculator or laptop. It is also the ability to arrive at a number through various sources and then validating them.
How to judge ability to triangulate numbers and do back of the envelope calculations?
Guess estimate comes to your rescue here. Just ask the candidate to perform the guess estimate on a paper and then ask him to validate the number through an alternate approach.
Communication skills – Ability to tell stories based on numbers
Any analyst is only as good as he can communicate. If a person can not take the complex world of numbers and create a meaningful story out of it, he will always be looked upon as a nerd. He can be a good analyst, but not the best one. Ability to create a story and present it almost has an equal, if not higher influence on your customers and hence increases the chances of success of any analytics project.
How do you judge communication skills?
You can get a sense on this through the entire interview. If this is very critical to the role you are evaluating for, you can provide datasets in excel and ask the person to present some open ended questions
Hopefully, this framework will help you for any analyst hiring in future. In case you have some suggestions, do let me know.
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According to Silicon Alley Insider, Credit Suisse analyst Bill Shope has been doing some research on Apple. His conclusions seem pretty reasonable…with some caveats. Here are his findings and our thoughts below:
New iPods: “More likely.” Apple refreshes its iPod line in the fall, and there’s no reason it won’t this year. To compete better with the cheaper iPhone, Apple could offer higher-capacity iPods at lower prices, one possible explanation for its warning about low gross margins.
Refreshed MacBooks: “More likely.” No major shape/size changes, but faster laptops at lower prices.
iPhone nano: “Less likely.” It makes sense that Apple would extend the iPhone family the way it’s done with its computers, iPods, etc. And a cheaper, slimmed-down iPhone could reach a broader audience than today’s. Just not so soon after it launched the iPhone 3G, which has strong demand.
Super-cheap laptop: “Less likely.” Eventually, Apple will need to come out with a laptop under $800 to tap into new markets. But Shope’s conversations with Apple “suggest that the company may not be ready for such a drastic change in product strategy in the near-term.”
Super-cheap desktop: “Less likely.” An all-in-one, not the Mac mini, which would expose Apple to the “sweet spot of the desktop market fairly quickly.” Just not convinced Apple is ready to play in the “discount PC market” yet.
Mac TV: “Even less likely,” a “long shot.” Apple could skip the set-top box by building its Apple TV software into a flat-panel TV. While Shope (and we) would probably be buyers, he thinks “this seems a bit outside of Apple’s normal sphere of business for now.”
Tablet: Disagree, won’t happen until 2009 unless you count enhanced iPod Touches. We would like to see something like the Nokia N810 specs but hopes are low.
iPhone Nano: No, no, no – never. Is $200 really too much to spend on an iPhone? In some places it is already free with an expensive plan. Is the iPhone too big? Not really. If anything, Apple will go more upscale in the coming year and the current devices will be the low end.
Super cheap laptop? This is Apple. No. But somewhat smaller and less expensive are realistic longer term possibilities.
Super cheap desktop? As much as we’d like to see one, nope. Psystar-like specs, mass produced in a nice enclosure for $400 would be nice, however significant specs updates to the Mini without price movement would cover this market and are much more likely.
AppleTV? Actually, unlike Shope, we think a game change is very likely. If Apple could cut deals with HD screen manufacturers across the board (like it did with movies studios) and at the same time beef up the hardware to do 1080p, Apple could turn its hobby into a serious business. We know Apple wants into this field so badly that it is willing to subsidize the cost. Components are costing less and less and at some point it will cost about as much 20 movies or a few seasons of a TV series. The opportunity to entirely subsidize the cost of the device will arrive at some point soon. The biggest obstacle? The state of US broadband. Bottom line, look for movement – there are many opportunities ahead. —-Also, adding a gaming component to the AppleTV would be cool but a long way off – a deal with Nintendo to bundle the AppleTV with the Wii might be cool.
We would also like to see some more work on Apple’s Pro Hardware. Most of this equipment hasn’t beeen significantly upgraded since PowerPC days. What do you think?
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Multiple reports suggest that what could have been a massive threat to iPhone sales has now been resolved.
One interpretation of an executive order by President Trump would have banned Apple from doing any business with WeChat owner Tencent, even in China. It was calculated that this could have cost Apple as much as 30% of its global iPhone revenue …Background
Earlier in the month, President Trump signed an executive order banning US companies from doing business with Chinese companies ByteDance and Tencent, owners of TikTok and WeChat respectively. The wording was unclear, with some suggesting this meant that Apple would have to remove WeChat from all its App Stores, including China.
The potential consequences of this would have been dramatic. Almost nobody in China would buy an iPhone if it can’t run WeChat for reasons explained here, and China is Apple’s second-largest market after the US. Noted Apple analyst Ming-Chi Kuo estimated that this could slash global iPhone sales by as much as 30%.
Apple warned the White House about the ‘severe’ implications of banning WeChat, and thankfully, the administration appears to have finally listened.Full-scale threat to iPhone sales reportedly ended
A Bloomberg report said that the administration had since realized the consequences of an all-out ban.
The Trump administration is privately seeking to reassure U.S. companies including Apple Inc. that they can still do business with the WeChat messaging app in China, according to several people familiar with the matter, two weeks after President Donald Trump ordered a U.S. ban on the Chinese-owned service.
In recent days, senior administration officials have been reaching out to some companies, realizing that the impact of an all-out ban on the popular app, owned by China’s Tencent Holdings Ltd., could be devastating for U.S. technology, retail, gaming, telecommunications and other industries, people familiar with the discussions said.
Analysts Wedbush said it had heard the same from its own political contacts.
This is in line with our view and thesis based on recent discussions with contacts within the Beltway that the WeChat ban will not negatively impact or disrupt Apple’s iPhone ecosystem within the key China market, which represents roughly 20% of overall upgrades over the next 12 to 18 months. While the WeChat ban is within the US (App Store), importantly for Apple we believe Chinese consumers should see no disruption with this app which is key especially heading into the company’s long awaited 5G iPhone 12 supercycle ready to launch in early October.
It’s also consistent with greatly-improved supply-chain reports after the earlier uncertainty.
Our recent Asia supply chain checks conducted by our TMT team show a discernible uptick in forecasts for iPhone 12
The firm says that this puts the iPhone 12 back on track to be a defining moment in the company’s history.
Apple has a “once in a decade” opportunity over the next 12 to 18 months as we estimate roughly 350 million of Cupertino’s 950 million iPhones worldwide are in the window of an upgrade opportunity. China remains a key ingredient in Apple’s recipe for success as we estimate roughly 60 million to 70 million iPhone upgrades will be coming from this region over the coming year […]
We believe iPhone 12 represents the most significant product cycle for Cook & Co. since iPhone 6 in 2014 and will be another defining chapter in the Apple growth story.
The change doesn’t completely remove the threat to iPhone sales – Kuo estimates an impact of 3-6% remains – but the very much larger threat appears to have been averted.
Photo: Karl Mondon/Bay Area News Group
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Well, one crypto-analyst certainly thinks so, with popular YouTuber Lark Davis recently laying out a practical guide for the same.
Before jumping right into it, it’s worth discussing the elephant in the room – How much money is required, irrespective of the age to get financial freedom? Here’s what this New Zealand-based crypto bull had to say about this,
“Classic calculation is 25 X your annual expenses based on withdrawing 4% annually. IE your expenses are $50,000 a year then you’ll need 1.25 million. Just 1.25 million.”
“IE 250k in Anchor would give your 50k a year passive. Still though the more the better.”
For a deeper perspective on expenses and savings, here’s how the median disposable income for residents aged 65 and over across the world look like,
Countries such as the USA, with a median retiree income of $26,250, are ranked third in the world, on par with Switzerland, Canada, and Austria. The point is, these figures will vary based on which country one is based in.
Now comes the hard bit, how to get the money?
Getting enough for retirement, whether early or not, is not an overnight endeavor. It requires a lot of patience and time, with “the most common way” being by “cutting the fat,” according to Davis.
In addition to this, consider the spending optimization attribute as well. He reiterated,
“Review your budget and ask yourself the hard questions. The more you can invest and sooner, the more likely it will be that you can retire early.”
Post the saving stage comes the investing part. As covered previously, Davis has always highlighted the importance of dollar-cost average into safer cryptocurrencies like Bitcoin, Ethereum, Chainlink, Aave. This time is no different.
Ergo, he hinted at the time in the market versus timing the market approach. What’s more, the analyst repeated that “the younger you are the more risk you can take,” with Davis cautioning his followers of the potential risks by adding,
“You can flush a year of home-brewed coffee savings down the drain in minutes on leverage trading, meme coins, and degen DeFi.”
Having said that, Davis has in the past stated that altcoins have the best shot at massive returns on investments. He tweeted,
— Lark Davis (@TheCryptoLark) July 13, 2023
Consider this – At the time of writing, BTC was noting YTD returns of 18.23%. On the other hand, the likes of ETH, LINK, DOT, and ADA were registering figures of 155%, 44%, 27%, and 562%.
Ethereum, Chainlink, Polkadot, and Cardano, at press time, had all appreciated significantly when compared to the world’s largest cryptocurrency, despite recent market corrections being accounted for. Ergo, altcoins might not be a bad idea if one is looking to save up money for retirement.
It’s also worth noting that like in the past, Davis again shared his optimism with respect to earning passive income and staking.
The analyst concluded the aforementioned video by stating,
“…retiring on crypto in your 20’s or 30’s or 40’s or whenever is indeed possible. And you can do it, just be aware that risks remain and you need to keep a calm rational investor-focused mindset to make it happen.”
Now, that might be difficult these days, especially since it has faced a lot of scrutiny from different regulators as well as individuals lately. Here, it should be pointed out that despite such skepticism, the market has come a long way. The fact that analysts are discussing crypto as a retirement option is a big deal, especially since mainstream reports a few years ago were saying that early retirees won’t EVER touch Bitcoin and other cryptos.
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